Dry electrodes for electroencephalography

ABSTRACT

An electroencephalography (EEG) system includes a dry electrode design having a jagged, angular, comb, etc. shaped support housing. Each dry electrode housing includes multiple electrodes where each electrode has multiple contacts for scalp placement with minimal interference from hair. Signals from individual contacts may be disregarded and each housing may provide one or more aggregated signals for data analysis. Each electrode may be placed in close proximity with neighboring electrodes as no conductive gel is required and may be attached to the scalp using straps, elastic cap, spring-type materials, tape, etc. The dry electrode design effectively measures bio-signals including neurological activity.

TECHNICAL FIELD

The present disclosure relates to electrodes for electroencephalography(EEG).

DESCRIPTION OF RELATED ART

Conventional EEG systems use scalp level electrode attachment to monitorneurological activity. Conductive gels and pastes are often appliedbefore placement of the scalp electrodes to improve sensitivity.However, application of conductive gels and pastes is often inconvenientand time consuming. Furthermore, conductive gels and pastes can oftenbleed between neighboring electrodes and cause signal contamination.

Some efforts have been made in the development of dry electrodes.However, available dry electrodes have a variety of limitations.Consequently, it is desirable to provide improved dry electrodes forEEG.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may best be understood by reference to the followingdescription taken in conjunction with the accompanying drawings, whichillustrate particular example embodiments.

FIGS. 1A-1B illustrate examples of EEG caps.

FIG. 2 illustrates one example of an EEG electrode.

FIG. 3 illustrates one example of an EEG electrode contact.

FIGS. 4A-4B illustrate examples of techniques for selecting an electrodesignal.

FIG. 5 illustrates one technique for selecting a local signal.

FIG. 6 illustrates one example of a system for performing distributedneuro-response data collection and analysis.

FIG. 7 illustrates one example of a system that can be used to implementone or more mechanisms.

DESCRIPTION OF PARTICULAR EMBODIMENTS

Reference will now be made in detail to some specific examples of theinvention including the best modes contemplated by the inventors forcarrying out the invention. Examples of these specific embodiments areillustrated in the accompanying drawings. While the invention isdescribed in conjunction with these specific embodiments, it will beunderstood that it is not intended to limit the invention to thedescribed embodiments. On the contrary, it is intended to coveralternatives, modifications, and equivalents as may be included withinthe spirit and scope of the invention as defined by the appended claims.

For example, the techniques and mechanisms of the present invention willbe described in the context of particular types of sensor materials.However, it should be noted that the techniques and mechanisms of thepresent invention apply to a variety of different types of materials. Itshould be noted that various mechanisms and techniques can be applied toany type of stimuli. In the following description, numerous specificdetails are set forth in order to provide a thorough understanding ofthe present invention. Particular example embodiments of the presentinvention may be implemented without some or all of these specificdetails. In other instances, well known process operations have not beendescribed in detail in order not to unnecessarily obscure the presentinvention.

Various techniques and mechanisms of the present invention willsometimes be described in singular form for clarity. However, it shouldbe noted that some embodiments include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. For example, a system uses a processor in a variety ofcontexts. However, it will be appreciated that a system can use multipleprocessors while remaining within the scope of the present inventionunless otherwise noted. Furthermore, the techniques and mechanisms ofthe present invention will sometimes describe a connection between twoentities. It should be noted that a connection between two entities doesnot necessarily mean a direct, unimpeded connection, as a variety ofother entities may reside between the two entities. For example, aprocessor may be connected to memory, but it will be appreciated that avariety of bridges and controllers may reside between the processor andmemory. Consequently, a connection does not necessarily mean a direct,unimpeded connection unless otherwise noted.

Overview

An electroencephalography (EEG) system includes a dry electrode designhaving a jagged, angular, comb, etc. shaped support housing. Each dryelectrode housing includes multiple electrodes where each electrode hasmultiple contacts for scalp placement with minimal interference fromhair. Signals from individual contacts may be disregarded and eachhousing may provide one or more aggregated signals for data analysis.Each electrode may be placed in close proximity with neighboringelectrodes as no conductive gel is required and may be attached to thescalp using straps, elastic cap, spring-type materials, tape, etc. Thedry electrode design effectively measures bio-signals includingneurological activity.

Example Embodiments

EEG measures electrical activity associated with post synaptic currentsoccurring in the milliseconds range. Subcranial EEG can measureelectrical activity with the most accuracy, as the bone and dermallayers weaken transmission of a wide range of frequencies. Nonetheless,surface EEG provides a wealth of electrophysiological information ifanalyzed properly.

Conventional EEG systems use wet electrodes that require skinpreparation and application of conductive gels. An example of wetelectrodes are silver/silver chloride (Ag/AgCl) electrodes.Silver/silver chloride (Ag/AgCl) electrodes have been widely usedbecause of their low cost and stability, but are often inconvenient anduncomfortable. They require conductive gels that can cause allergicreactions and are typically impractical for use outside of controlledenvironments. Conductive gels are also ineffectiveness where longrecording times are required, as gels dry out and lose efficacy overtime. Furthermore, wet electrodes often require significant physicalseparation from neighboring electrodes because conductive gels can bleedonto neighboring electrodes. This limits the resolution EEG scalpmeasurements as a limited number of electrodes and associated contactscan be used.

Consequently, some efforts have been made in developing dry electrodes.Dry electrodes can have either a conductive or insulating contactmaterial and are often referred to as dry active electrodes. Inparticular embodiments, a capacitive coupling between the scalp and theelectrode is created so that the signal is transferred to the electrodeby a capacitive conduction mechanism. Dry electrode sensor material maybe an inert metal like stainless steel or gold. Alternatively, the dryelectrode sensor material may be an insulator.

Dry electrodes, however, have significantly higher skin electrodeimpedance. For dry electrodes to be effective, the techniques andmechanisms of the present invention contemplate mechanisms forcompensating for the high impedance. Impedance may vary and/or fluctuatein regions having a significant number of hair follicles. Impedance mayalso change in region having high skin elasticity. To compensate forvariable and/or flucating impedance, the techniques and mechanisms ofthe present invention provide a jagged shaped support structure for eachelectrode. Each electrode is provided with multiple contact points orcontact pads. In particular embodiments, each electrode selects alocally optimal or preferred signal from the different signals receivedfrom the multiple contacts. In some examples, the preferred signal maybe a signal having the most consistent and/or highest amplitude during aset of calibrations. According to various embodiments, the locallyoptimal or preferred signal is amplified and sent to a transmitter. Asystem also may select a regionally preferred signal from a group ofelectrodes. According to various embodiments, regionally optimal signalsare selected from a group locally optimal signals.

Each electrode may be fabricated using semiconductor manufacturingprocesses to provide individual electrode integrated circuits. Accordingto various embodiments, each contact has a diameter of 0.5 mm-6 mm. Inparticular embodiments, each contact has a width of 0.5 mm and a lengthof 2 mm and a thickness of 2 mm. Smaller contacts more easily navigatethrough hair to reach the scalp surface. However, too small a contactleads to irritation, and a small contact still does not guarantee thatit will reach the scalp. Larger contacts are more comfortable and canprovide more surface area for measurement, but can be limited in theirability to read a uniform signal. A large surface contact can notmeasure a consistent signal due to hair and motion that decouples thecontact from the skin surface.

According to various embodiments, each contact is coated with a materialto allow for easy navigation through hair while also resistingcorrosion. In particular embodiments, each contact is coated with one ormore 50 nm-250 nm layers of titanium oxide (TiO₂). TiO₂ is inert on mostphysiologic media and effectively resists corrosion. In other examples,silicon nitride (Si₃N₄) can also be used. Each contact may be connectedto selection circuitry to allow an electrode, or a system, to select oneor more preferred signals of the electrode. In some instances, no signalmay be suitable. Individual electrode may also include filters,capacitors, diodes, power supplies, and amplifiers, and transmitters.

The EEG electrodes can be used to measure spontaneous EEG. The bandwidthof the measurement can range from 0.05 Hz to 80 Hz. The amplitude of theEEG signal can range from 50 uV-250 uV with sensitivity of 10 uV/mm.Evoked potentials (EP) are time-locked averages of neurologicalactivity. According to various embodiments, EP amplitudes range from0.05 -30 uV. It is recognized that both wet and dry electrodes can beused to efficiently measure a variety of signals resulting fromneurological activity including spontaneous EEG and EP. According tovarious embodiments, portable EEG with dry electrodes provide a largeamount of neuro-response information.

FIGS. 1A-1B illustrate particular examples of mechanisms for placing EEGdry electrodes on a surface such as the scalp of a subject. According tovarious embodiments, the distributed neuro-response data collectionmechanism includes multiple EEG dry electrodes including electrodes 111,113, and 115. In particular embodiments, the EEG dry electrodes arespring loaded or cushion loaded operate to detect neurological activitywith minimal interference from hair. The EEG dry electrodes also do notrequire use of any electrically conductive gels. The EEG dry electrodesmay each be configured on a longitudinal or latitudinal zig zagarrangement. Each arrangement may have multiple EEG dry electrodes. EachEEG dry electrode may have multiple contacts. According to variousembodiments, distributed neuro-response data collection mechanism alsoincludes EOG sensors such as sensor 121 used to detect eye movements.

The data collection mechanism may also include a transmitter and/orreceiver to send collected neuro-response data to a data analysissystem. In some examples, a transceiver 141 transmits all collectedmedia such as video and/or audio, neuro-response, and sensor data to adata analyzer. In other examples, a transceiver 141 transmits onlyinterested data provided by a filter 143. In other examples, thetransceiver 141 also receives information that can be provided to a useror used to modify a system. The filter 143 can remove noise as well asuninteresting portions of collected data. The filter 143 cansignificantly reduce network usage and can be valuable when limitednetwork resources are available. In some examples, the transceiver canbe connected to a computer system that then transmits data over a widearea network to a data analyzer. In other examples, the transceiversends data over a wide area network to a data analyzer. Other componentssuch as fMRI and MEG that are not yet portable but may become portableat some point may also be integrated into a headset, cap, band, clips,etc.

The headset, cap, band, clips, comb, etc., may be configured in a verydiscrete manner. It should be noted that some components of aneuro-response data collection mechanism have not been shown forclarity. For example, a battery may be required to power components suchas cameras and sensors and wiring from the battery are not shown.Similarly, a transceiver may include an antenna that is similarly notshown for clarity purposes.

According to various embodiments, a comb type distributed neuro-responsedata collection mechanism including multiple EEG dry electrodes is shownin FIG. 1B. The comb structure includes electrodes 161, 163, and 165. Inparticular embodiments, the EEG dry electrodes operate to detectneurological activity with minimal interference from hair. The EEG dryelectrodes also do not require use of any electrically conductive gels.According to various embodiments, distributed neuro-response datacollection mechanism also includes EOG sensors such as sensor 171 usedto detect eye movements.

The data collection mechanism may also include a transmitter and/orreceiver to send collected neuro-response data to a data analysissystem. In some examples, a transceiver 191 transmits all collectedmedia such as video and/or audio, neuro-response, and sensor data to adata analyzer. In other examples, a transceiver 191 transmits onlyinterested data provided by a filter 193. In other examples, thetransceiver 191 also receives information that can be provided to a useror used to modify a system. The filter 193 can remove noise as well asuninteresting portions of collected data. The filter 193 cansignificantly reduce network usage and can be valuable when limitednetwork resources are available. In some examples, the transceiver canbe connected to a computer system that then transmits data over a widearea network to a data analyzer. In other examples, the transceiversends data over a wide area network to a data analyzer. Other componentssuch as fMRI and MEG that are not yet portable but may become portableat some point may also be integrated into a headset, cap, band, clips,etc.

FIG. 2 illustrates one example of an electrode having multiple contactsand/or sensors. According to various embodiments, each contact 201, 203,205, and 207 has a diameter of 0.05 mm-6 mm. In particular embodiments,each contact is cylindrical and has a spherical tip. In other examples,each contact or sensor has a rectangular cross section and a conicaltip. Other cross sections and structures are possible. Smaller contactsmore easily navigate through hair to reach the scalp surface. However,too small a contact leads to irritation, and a small contact still doesnot guarantee contact with the scalp.

Shielding is provided to reduce electromagnetic interference onelectrode circuitry. According to various embodiments, selectioncircuitry 211 is provided to select the electrode having the highestsignal quality. In some examples, hair follicles may prevent firmcontact between particular sensors 201, 203, 205, and 207 and the scalp.In particular embodiments, selection circuitry 211 identifies the sensorproviding the signal with the highest average amplitude. In otherexamples, selection circuitry 211 identifies the sensor providing thesignal closest to the expected signal. In other examples, selectioncircuitry may not be provided and local selection of a sensor signal fora particular electrode may be performed by an EEG system aftertransmission of all signals to the EEG system.

According to various embodiments, a preamplifier 223 may be providedbefore or after selection circuitry to strengthen a signal detected bycontacts 201, 203, 205, and/or 207. According to various embodiments,the pre-amplifier gain can be set to 2-50 kv/V for use with dryelectrodes. Power source 221 may be a battery, a radio frequency powersource, a piezo-electric power source, etc. In particular embodiments, afilter 231 may be a simple low pass, high pass, or band pass filter usedto remove signals falling outside of the detectable EEG signal frequencyranges. In other examples, the filter can be used to remove knownartifacts generated by movements such as jaw movements or blinking.

Transmitter 233 sends detected signals to an EEG system. In someexamples, the transmitter 233 is a wired or wireless transceiver thatdigitizes signals and transmits them to a computing system afteramplification and filtering. Wired systems may require extensiveshielding particularly if the EEG electrodes are used in conjunctionwith other systems such as fMRI.

FIG. 3 illustrates one example of a group of electrodes having multiplecontacts and/or sensors. According to various embodiments, eachelectrode 301, 321, and 341 includes corresponding skin and/or scalpcontacts. Electrode 301 includes contacts 303, 305, and 307. Electrode321 includes contacts 323, 325, and 327. Electrode 341 includes contacts343, 345, and 347.

According to various embodiments, each contact has a size ranging from0.1 mm-5 mm. In particular embodiments, each contact is cylindrical andhas a spherical tip. In other examples, each contact or sensor has arectangular cross section and a rectangular tip. A variety ofconfigurations are possible. Smaller contacts more easily navigatethrough hair to reach the scalp surface. However, too small a contactleads to irritation, and a small contact still does not guarantee thatit will reach the scalp.

Shielding is provided to reduce electromagnetic interference onelectrode circuitry. According to various embodiments, each electrode301, 321, and 341 includes corresponding selection circuitry 309, 329,and 349. In particular embodiments, selection circuitry 309, 329, and349 identify locally preferred signals. In some examples, signals havinggood signal to noise characteristics are selected by selection circuitry309, 329, and 349 at each electrode. In other examples, selectioncircuitry 309, 329, and 349 identify one or more signals providing thesignal closest to the expected signal. In other examples, selectioncircuitry may not be provided and local selection of a sensor signal fora particular electrode may be performed by regional signal selectioncircuitry 363. According to various embodiments, selection circuitry309, 329, and 349 select locally preferred signals while regional signalselection circuitry 363 select regionally preferred signals from a groupof electrodes such as electrodes 301, 321, and 341.

According to various embodiments, amplifiers and/or preamplifiers 313,333, and 353 may be provided before or after selection circuitry tostrengthen a signal detected by contacts 303, 305, 307, 323, 325, 327,and 343, 345, and 347. According to various embodiments, thepre-amplifier gain can be set to 2-50 kv/V for use with dry electrodes.Power sources 311, 331, and 351 may be batteries, radio frequency powersources, piezo-electric power sources, etc. In particular embodiments,filters may also be provided. Filter 315, 335, and 355 may be low pass,high pass, band pass filters, etc., used to remove signals fallingoutside of the detectable EEG signal frequency ranges. In otherexamples, the filters can be used to remove known artifacts generated bymovements such as jaw movements or blinking.

Transmitters 317, 337, and 357 send detected signals to an EEG system.In some examples, the transmitter 317, 337, and 357 are wired orwireless transceivers that digitize signals and transmit them to acomputing system after amplification and filtering. The transceivers mayalso receive signals from an EEG system to dynamically modify frequencyranges detected or amplifier gains to be applied. Wired systems mayrequire extensive shielding particular if the EEG electrodes are used inconjunction with other systems such as fMRI. According to variousembodiments, individual electrodes 301, 321, and 341 are arranged on ajagged structure electrode housing structure 371. According to variousembodiments, the jagged structure 371 is a longitudinally orlatitudinally arranged zig zag or wave structure configured to displaceas much hair as possible as EEG electrodes are placed on the scalp. Zigzag configurations may be horizontally or vertically placed. An EEGsystem may also include a receiver 361 to obtain signals from individualelectrodes 301, 321, and 341. Regional signal selection circuitry 363selects preferred signals from groups of electrodes. According tovarious embodiments, hundreds of electrodes and thousands of contactsmay be placed on an individual scalp, and the regional signal selectioncircuitry 363 remove signals from sensors having poor or fluctuatingcontact with the scalp. In other examples, far fewer or a far greaternumber of electrodes can be used.

The locally selected and the regionally selected signals are provided toa data analyzer 365. Data analysis may include intra-modality responsesynthesis and cross-modality response synthesis to enhance effectivenessmeasures. It should be noted that in some particular instances, one typeof synthesis may be performed without performing other types ofsynthesis. For example, cross-modality response synthesis may beperformed with or without intra-modality synthesis.

FIG. 4A illustrates one mechanism for selecting a local signal. At 401,reference signals are obtained. According to various embodiments,reference signals may be ground signals used as a reference point formeasured signals. At 403, controlled stimulus materials are provided. Inparticular embodiments, controlled stimulus materials are materialsknown to elicit particular neurological responses. In other examples,stimulus materials for analysis are provided. At 405, signals areobtained from multiple contacts associated with an electrode. Inparticular embodiments, each electrode includes multiple contactsarranged in a tooth shaped support structure to allow effective scalpcontact through hair.

According to various embodiments, the worst signals are removed at 407.In particular embodiments, signals showing amplifier blockingcharacteristics are removed. Anything having a significant amount ofhigh frequency noise, (e.g. >40 Hz) can also be eliminated. In someexamples, anything pinning characteristics associated with constantdecreasing amplitude are removed as the decrease in amplitude mayindicate imminent detachment of the contact from the scalp. In otherembodiments, having low signal to noise ratios are disregarded. In stillother embodiments, signals having poor drift and jitter characteristicsare removed. At 413, remaining contacts are averaged to provide a localsignal. In some examples, signals from four remaining contacts areaveraged to provide an aggregated signal. A selection, averaging, orother combination of signals is referred to herein as an aggregatedsignal. In some examples, two signals having good characteristics areaveraged to provide an aggregated signal.

FIG. 4B illustrates another mechanism for selecting a local signal. At451, reference signals are obtained. According to various embodiments,reference signals may be ground signals used as a reference point formeasured signals. At 453, controlled stimulus materials are provided. Inparticular embodiments, controlled stimulus materials are materialsknown to elicit particular neurological responses. In other examples,stimulus materials for analysis are provided. At 455, signals areobtained from multiple contacts associated with an electrode. Inparticular embodiments, each electrode includes multiple contactsarranged in a tooth shaped support structure to allow effective scalpcontact through hair.

According to various embodiments, local signals with the closestcorrelation to expected signals are identified at 457. In particularembodiments, signals having the highest average amplitude at determinedat 459. Signals having the highest signal to noise ratio may also beidentified at 461. At 463, a contact providing the local signal isselected.

FIG. 5 illustrates one mechanism for selecting a local and regionalsignal. At 501, select local signals are obtained. According to variousembodiments, local signals having poor characteristics are removed at503. In particular embodiments, signals associated with amplifierblocking or pinning are removed. Signals showing characteristicscorresponding with imminent detachment of the contact from the scalp mayalso be removed 505. In other embodiments, signals having low signal tonoise ratios are disregarded. At signals having the highest averageamplitude may be determined. Signals having the highest signal to noiseratio may also be identified. At 507, regional signals are selected fromelectrodes in the same electrode housing. According to variousembodiments, each electrode housing may include 2-10 electrodes, whereeach individual electrode includes multiple contacts.

Each electrode housing may be a zigzag, rectangular, cylindrical, comb,etc. type structure arranged to allow electrode contact with the scalpwith minimal interference from hair. In particular embodiments, eachhousing ranges from 0.2 mm to 2 cm in length, 1 mm to 1 cm in width, and0.2 mm to 2 cm in thickness. In other particular embodiments, eachhousing ranges from 1 mm to 3 cm in diameter and 1.1 mm to 2 cm inthickness. Configurations may vary widely depending on manufacturingtechnologies and materials. According to various embodiments, thenon-eliminated signals or selected signals are averaged at 509. In someexamples, one signal may be selected as the desired signal, althoughtaking remaining selected signals from the housing may allow for furthernoise reduction. At 511, selected, averaged, and/or aggregated signalsfrom the electrode housing are sent for analysis.

FIG. 6 illustrates one example of neuro-response data collection usingdry electrodes. At 601, user information is received from a subjectprovided with a neuro-response data collection mechanism. According tovarious embodiments, the subject sends data including age, gender,income, location, interest, ethnicity, etc. after being provided with anEEG cap including EEG electrodes, EOG sensors, cameras, recorders,network interfaces, and a global position system (GPS) device integratedinto an unobtrusive device that can be worn during typical activities.

At 603, neuro-response data, video and audio recorded data, timinginformation, and/or location information, etc., is received from thesubject neuro-response data collection mechanism. According to variousembodiments, EEG, EOG, pupillary dilation, facial emotion encoding data,video, images, audio, GPS data, timestamps, etc., are transmitted fromthe subject to a neuro-response data analyzer. In particularembodiments, data is filtered and compressed prior to transmission. Forexample, only video and audio corresponding to neuro-logically salientevents are transmitted to save on network bandwidth. According tovarious embodiments, neuro-response and associated data is transmitteddirectly from an EEG cap wide area network interface to a data analyzer.In particular embodiments, neuro-response and associated data istransmitted to a computer system that then performs compression andfiltering of the data before transmitting the data to a data analyzerover a network.

According to various embodiments, data is also passed through a datacleanser to remove noise and artifacts that may make data more difficultto interpret. According to various embodiments, the data cleanserremoves EEG electrical activity associated with blinking and otherendogenous/exogenous artifacts. Data cleansing may be performed beforeor after data transmission to a data analyzer.

At 605, stimulus material is identified. According to variousembodiments, stimulus material is identified based on user input. Forexample, a user watching a particular movie may enter the title of themovie along with how and where it was viewed. Alternatively, videorecording may be analyzed using text, facial, brand, video, image, andaudio recognition algorithms to determine what the user was viewing. Eyetracking movements can determine where user attention is focused at anygiven time. Although that eye movements do occur when attention isdiverted, it is recognized that focused attention typically occurs wheneye position is focused in the forward direction. Consequently, the EEGcap and video camera direction typically coincide with the direction ofuser attention. EEG data may also be tagged to indicate correspondencewith particular video and audio events. According to variousembodiments, a user walking down a supermarket aisle may directattention to certain products that are identified using video recordingsand correlated with neuro-response measures to determine theeffectiveness of product labeling.

At 607, neuro-response data is synchronized with timing, location, andother stimulus material data. According to various embodiments,neuro-response data such as EEG and EOG data is tagged to indicate whatthe subject is viewing or listening to at a particular time.

At 609, data analysis is performed. Data analysis may includeintra-modality response synthesis and cross-modality response synthesisto enhance effectiveness measures. It should be noted that in someparticular instances, one type of synthesis may be performed withoutperforming other types of synthesis. For example, cross-modalityresponse synthesis may be performed with or without intra-modalitysynthesis.

A variety of mechanisms can be used to perform data analysis 609. Inparticular embodiments, a stimulus attributes repository is accessed toobtain attributes and characteristics of the stimulus materials, alongwith purposes, intents, objectives, etc. In particular embodiments, EEGresponse data is synthesized to provide an enhanced assessment ofeffectiveness. According to various embodiments, EEG measures electricalactivity resulting from thousands of simultaneous neural processesassociated with different portions of the brain. EEG data can beclassified in various bands. According to various embodiments, brainwavefrequencies include delta, theta, alpha, beta, and gamma frequencyranges. Delta waves are classified as those less than 4 Hz and areprominent during deep sleep. Theta waves have frequencies between 3.5 to7.5 Hz and are associated with memories, attention, emotions, andsensations. Theta waves are typically prominent during states ofinternal focus.

Alpha frequencies reside between 7.5 and 13 Hz and typically peak around10 Hz. Alpha waves are prominent during states of relaxation. Beta waveshave a frequency range between 14 and 30 Hz. Beta waves are prominentduring states of motor control, long range synchronization between brainareas, analytical problem solving, judgment, and decision making. Gammawaves occur between 30 and 60 Hz and are involved in binding ofdifferent populations of neurons together into a network for the purposeof carrying out a certain cognitive or motor function, as well as inattention and memory. Because the skull and dermal layers attenuatewaves in this frequency range, brain waves above 75-80 Hz are difficultto detect and are often not used for stimuli response assessment.

However, the techniques and mechanisms of the present inventionrecognize that analyzing high gamma band (kappa-band: Above 60 Hz)measurements, in addition to theta, alpha, beta, and low gamma bandmeasurements, enhances neurological attention, emotional engagement andretention component estimates. In particular embodiments, EEGmeasurements including difficult to detect high gamma or kappa bandmeasurements are obtained, enhanced, and evaluated. Subject and taskspecific signature sub-bands in the theta, alpha, beta, gamma and kappabands are identified to provide enhanced response estimates. Accordingto various embodiments, high gamma waves (kappa-band) above 80 Hz(typically detectable with sub-cranial EEG and/ormagnetoencephalograophy) can be used in inverse model-based enhancementof the frequency responses to the stimuli.

Various embodiments of the present invention recognize that particularsub-bands within each frequency range have particular prominence duringcertain activities. A subset of the frequencies in a particular band isreferred to herein as a sub-band. For example, a sub-band may includethe 40-45 Hz range within the gamma band. In particular embodiments,multiple sub-bands within the different bands are selected whileremaining frequencies are band pass filtered. In particular embodiments,multiple sub-band responses may be enhanced, while the remainingfrequency responses may be attenuated.

An information theory based band-weighting model is used for adaptiveextraction of selective dataset specific, subject specific, taskspecific bands to enhance the effectiveness measure. Adaptive extractionmay be performed using fuzzy scaling. Stimuli can be presented andenhanced measurements determined multiple times to determine thevariation profiles across multiple presentations. Determining variousprofiles provides an enhanced assessment of the primary responses aswell as the longevity (wear-out) of the marketing and entertainmentstimuli. The synchronous response of multiple individuals to stimulipresented in concert is measured to determine an enhanced across subjectsynchrony measure of effectiveness. According to various embodiments,the synchronous response may be determined for multiple subjectsresiding in separate locations or for multiple subjects residing in thesame location.

Although a variety of synthesis mechanisms are described, it should berecognized that any number of mechanisms can be applied—in sequence orin parallel with or without interaction between the mechanisms.

Although intra-modality synthesis mechanisms provide enhancedsignificance data, additional cross-modality synthesis mechanisms canalso be applied. A variety of mechanisms such as EEG, Eye Tracking, GSR,EOG, and facial emotion encoding are connected to a cross-modalitysynthesis mechanism. Other mechanisms as well as variations andenhancements on existing mechanisms may also be included. According tovarious embodiments, data from a specific modality can be enhanced usingdata from one or more other modalities. In particular embodiments, EEGtypically makes frequency measurements in different bands like alpha,beta and gamma to provide estimates of significance. However, thetechniques of the present invention recognize that significance measurescan be enhanced further using information from other modalities.

For example, facial emotion encoding measures can be used to enhance thevalence of the EEG emotional engagement measure. EOG and eye trackingsaccadic measures of object entities can be used to enhance the EEGestimates of significance including but not limited to attention,emotional engagement, and memory retention. According to variousembodiments, a cross-modality synthesis mechanism performs time andphase shifting of data to allow data from different modalities to align.In some examples, it is recognized that an EEG response will often occurhundreds of milliseconds before a facial emotion measurement changes.Correlations can be drawn and time and phase shifts made on anindividual as well as a group basis. In other examples, saccadic eyemovements may be determined as occurring before and after particular EEGresponses. According to various embodiments, time corrected GSR measuresare used to scale and enhance the EEG estimates of significanceincluding attention, emotional engagement and memory retention measures.

Evidence of the occurrence or non-occurrence of specific time domaindifference event-related potential components (like the DERP) inspecific regions correlates with subject responsiveness to specificstimulus. According to various embodiments, ERP measures are enhancedusing EEG time-frequency measures (ERPSP) in response to thepresentation of the marketing and entertainment stimuli. Specificportions are extracted and isolated to identify ERP, DERP and ERPSPanalyses to perform. In particular embodiments, an EEG frequencyestimation of attention, emotion and memory retention (ERPSP) is used asa co-factor in enhancing the ERP, DERP and time-domain responseanalysis.

EOG measures saccades to determine the presence of attention to specificobjects of stimulus. Eye tracking measures the subject's gaze path,location and dwell on specific objects of stimulus. According to variousembodiments, EOG and eye tracking is enhanced by measuring the presenceof lambda waves (a neurophysiological index of saccade effectiveness) inthe ongoing EEG in the occipital and extra striate regions, triggered bythe slope of saccade-onset to estimate the significance of the EOG andeye tracking measures. In particular embodiments, specific EEGsignatures of activity such as slow potential shifts and measures ofcoherence in time-frequency responses at the Frontal Eye Field (FEF)regions that preceded saccade-onset are measured to enhance theeffectiveness of the saccadic activity data.

According to various embodiments, facial emotion encoding uses templatesgenerated by measuring facial muscle positions and movements ofindividuals expressing various emotions prior to the testing session.These individual specific facial emotion encoding templates are matchedwith the individual responses to identify subject emotional response. Inparticular embodiments, these facial emotion encoding measurements areenhanced by evaluating inter-hemispherical asymmetries in EEG responsesin specific frequency bands and measuring frequency band interactions.The techniques of the present invention recognize that not only areparticular frequency bands significant in EEG responses, but particularfrequency bands used for communication between particular areas of thebrain are significant. Consequently, these EEG responses enhance theEMG, graphic and video based facial emotion identification.

Integrated responses are generated at 611. According to variousembodiments, the data communication device transmits data to theresponse integration using protocols such as the File Transfer Protocol(FTP), Hypertext Transfer Protocol (HTTP) along with a variety ofconventional, bus, wired network, wireless network, satellite, andproprietary communication protocols. The data transmitted can includethe data in its entirety, excerpts of data, converted data, and/orelicited response measures. According to various embodiments, data issent using a telecommunications, wireless, Internet, satellite, or anyother communication mechanisms that is capable of conveying informationfrom multiple subject locations for data integration and analysis. Themechanism may be integrated in a set top box, computer system, receiver,mobile device, etc.

In particular embodiments, the data communication device sends data tothe response integration system. According to various embodiments, theresponse integration system combines analyzed and enhanced responses tothe stimulus material while using information about stimulus materialattributes. In particular embodiments, the response integration systemalso collects and integrates user behavioral and survey responses withthe analyzed and enhanced response data to more effectively measure andtrack distributed neuro-responses to stimulus materials. According tovarious embodiments, the response integration system obtains attributessuch as requirements and purposes of the stimulus material presented.

Some of these requirements and purposes may be obtained from a varietyof databases. According to various embodiments, the response integrationsystem also includes mechanisms for the collection and storage ofdemographic, statistical and/or survey based responses to differententertainment, marketing, advertising and otheraudio/visual/tactile/olfactory material. If this information is storedexternally, the response integration system can include a mechanism forthe push and/or pull integration of the data, such as querying,extraction, recording, modification, and/or updating.

The response integration system can further include an adaptive learningcomponent that refines user or group profiles and tracks variations inthe distributed neuro-response data collection system to particularstimuli or series of stimuli over time. This information can be madeavailable for other purposes, such as use of the information forpresentation attribute decision making. According to variousembodiments, the response integration system builds and uses responsesof users having similar profiles and demographics to provide integratedresponses at 611. In particular embodiments, stimulus and response datais stored in a repository at 613 for later retrieval and analysis.

According to various embodiments, various mechanisms such as the datacollection mechanisms, the intra-modality synthesis mechanisms,cross-modality synthesis mechanisms, etc. are implemented on multipledevices. However, it is also possible that the various mechanisms beimplemented in hardware, firmware, and/or software in a single system.FIG. 7 provides one example of a system that can be used to implementone or more mechanisms. For example, the system shown in FIG. 7 may beused to implement a data analyzer.

According to particular example embodiments, a system 700 suitable forimplementing particular embodiments of the present invention includes aprocessor 701, a memory 703, an interface 711, and a bus 715 (e.g., aPCI bus). When acting under the control of appropriate software orfirmware, the processor 701 is responsible for such tasks such aspattern generation. Various specially configured devices can also beused in place of a processor 701 or in addition to processor 701. Thecomplete implementation can also be done in custom hardware. Theinterface 711 is typically configured to send and receive data packetsor data segments over a network. Particular examples of interfaces thedevice supports include host bus adapter (HBA) interfaces, Ethernetinterfaces, frame relay interfaces, cable interfaces, DSL interfaces,token ring interfaces, and the like.

In addition, various very high-speed interfaces may be provided such asfast Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces,HSSI interfaces, POS interfaces, FDDI interfaces and the like.Generally, these interfaces may include ports appropriate forcommunication with the appropriate media. In some cases, they may alsoinclude an independent processor and, in some instances, volatile RAM.The independent processors may control such communications intensivetasks as data synthesis.

According to particular example embodiments, the system 700 uses memory703 to store data, algorithms and program instructions. The programinstructions may control the operation of an operating system and/or oneor more applications, for example. The memory or memories may also beconfigured to store received data and process received data.

Because such information and program instructions may be employed toimplement the systems/methods described herein, the present inventionrelates to tangible, machine readable media that include programinstructions, state information, etc. for performing various operationsdescribed herein. Examples of machine-readable media include, but arenot limited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks and DVDs;magneto-optical media such as optical disks; and hardware devices thatare specially configured to store and perform program instructions, suchas read-only memory devices (ROM) and random access memory (RAM).Examples of program instructions include both machine code, such asproduced by a compiler, and files containing higher level code that maybe executed by the computer using an interpreter.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. Therefore, the present embodiments are to be consideredas illustrative and not restrictive and the invention is not to belimited to the details given herein, but may be modified within thescope and equivalents of the appended claims.

1. A method, comprising: identifying stimulus material presented to auser; obtaining neuro-response data from a plurality ofelectroencephalography (EEG) dry electrodes placed on the scalp of theuser, each of the plurality of EEG dry electrodes having a plurality ofcontacts, wherein a first plurality of EEG dry electrodes are includedin a first housing and a second plurality of EEG dry electrodes areincluded in a second housing, the first plurality of EEG dry electrodeshaving a first plurality of contacts and the second plurality of EEG dryelectrodes having a second plurality of contacts; disregarding aplurality of signals from the first plurality of contacts; aggregatingremaining signals from the first plurality of contacts and provided anaggregated signal from the first housing to a data analyzer foranalysis.
 2. The method of claim 1, wherein remaining signals areaggregated by averaging remaining signals.
 3. The method of claim 1,wherein a plurality of signals having significant high frequency noise(>40 Hz) are disregarded.
 4. The method of claim 1, wherein a pluralityof signals having low signal to noise ratios are disregarded.
 5. Themethod of claim 1, wherein a plurality of signals exhibiting amplifierblocking are disregarded.
 6. The method of claim 1, wherein a pluralityof signals are disregarded by removing signals indicating imminentdetachment of an associated electrode from the scalp.
 7. The method ofclaim 1, wherein remaining signals are aggregated by identifying signalsfrom the first plurality of contacts most closely corresponding to anexpected signal.
 8. The method of claim 1, wherein the housing is ajagged shaped support structure.
 9. The method of claim 1, whereinperiodically a different plurality of signals are disregarded from thefirst plurality of contacts.
 10. The method of claim 9, wherein adifferent plurality of signals are disregarded from the first pluralityof contacts upon detecting poor characteristics exhibited by remainingsignals.
 11. An apparatus, comprising: a stimulus presentation deviceconfigured to present stimulus material to a user; a plurality ofelectroencephalography (EEG) dry electrodes configured for placement onthe scalp of the user, each of the plurality of EEG dry electrodeshaving a plurality of contacts, wherein a first plurality of EEG dryelectrodes are included in a first housing and a second plurality of EEGdry electrodes are included in a second housing, the first plurality ofEEG dry electrodes having a first plurality of contacts; selectioncircuitry configured to disregard a plurality of signals from the firstplurality of contacts and aggregate remaining signals from the firstplurality of contacts; a transmitter configured to provide an aggregatedsignal from the first housing to a data analyzer for analysis.
 12. Theapparatus of claim 11, wherein remaining signals are aggregated byaveraging remaining signals.
 13. The apparatus of claim 11, wherein aplurality of signals having significant high frequency noise (>40 Hz)are disregarded.
 14. The apparatus of claim 11, wherein a plurality ofsignals having low signal to noise ratios are disregarded.
 15. Theapparatus of claim 11, wherein a plurality of signals exhibitingamplifier blocking are disregarded.
 16. The apparatus of claim 11,wherein a plurality of signals are disregarded by removing signalsindicating imminent detachment of an associated electrode from thescalp.
 17. The apparatus of claim 11, wherein remaining signals areaggregated by identifying signals from the first plurality of contactsmost closely corresponding to an expected signal.
 18. The apparatus ofclaim 11, wherein the housing is a jagged shaped support structure. 19.The apparatus of claim 11, wherein periodically a different plurality ofsignals are disregarded from the first plurality of contacts.
 20. Theapparatus of claim 19, wherein a different plurality of signals aredisregarded from the first plurality of contacts upon detecting poorcharacteristics exhibited by remaining signals.
 21. An apparatus,comprising: means for identifying stimulus material presented to a user;means for obtaining neuro-response data from a plurality ofelectroencephalography (EEG) dry electrodes placed on the scalp of theuser, each of the plurality of EEG dry electrodes having a plurality ofcontacts, wherein a first plurality of EEG dry electrodes are includedin a first housing and a second plurality of EEG dry electrodes areincluded in a second housing, the first plurality of EEG dry electrodeshaving a first plurality of contacts and the second plurality of EEG dryelectrodes having a second plurality of contacts; means for disregardinga plurality of signals from the first plurality of contacts; means foraggregating remaining signals from the first plurality of contacts andprovided an aggregated signal from the first housing to a data analyzerfor analysis.